[CCoE Notice] Dissertation Defense: Asset Analytics of Smart Grid Infrastructure for Resiliency Enhancement

[Grayson, Audrey A]

Doctoral Dissertation Defense

Asset Analytics of Smart Grid Infrastructure for Resiliency Enhancement

By: Ali Arab

Advisors: Professor Suresh K. Khator
                  Professor Zhu Han

Committee Members: Dr. Gino Lim, Dr. Eylem Tekin, and Dr. Amin Khodaei

Date: Monday, April 20, 2015,      Time: 9:00 AM,       Location: ECE Large Conference Room

Abstract: Natural disasters, particularly the storms are still the vulnerable point of the electricity infrastructure as one of the most critical lifeline systems and of utmost importance to our daily lives.
First, a post-hurricane restoration model for power grid which considers the economics of disaster is introduced. The physical and economic constraints of the system, including unit commitment and restoration constraints, are incorporated in the proposed model. The aim is to restore the hurricane-related damages to electric power system infrastructure in an economic and customer-centered manner, without violating the physics of the system, in order to and mitigate the aftermath of natural disasters.

Second, a proactive resource allocation model for repair and restoration of potential damages to the power system infrastructure located on the path of an upcoming hurricane is proposed. The objective is to develop an efficient framework for system operators to minimize potential damages to power system components in a cost-effective manner. The problem is modeled as a two-stage stochastic integer program with recourse. The model is intended to improve proactive preparedness of the decision makers to cope with disasters, especially those of nature origins, in order to enhance the resilience and minimizes the restoration cost of electric power systems.
Third, a model is proposed to incorporate the impact of potential damage due to hurricane in the maintenance scheduling of the power infrastructure components located in hurricane prone areas. The power infrastructure deterioration process, as well as two competing and independent failure modes, i.e., failure due to loss of reliability and failure due to hurricane damages are integrated into model. Moreover, the interrelationship between the component, the grid, and the associated downtime cost dynamics are analyzed. The problem is modeled as a Markov decision process with perfect state information.

Fourth, the impact of El Nino/La Nina phenomenon which has shown to induce seasonal effects on hurricane arrivals in long-term climatological horizon is considered in asset management strategies of the electric power systems. An integrated infrastructure hardening and condition-based maintenance scheduling model for critical components of the power systems is developed. The partially observable Markov decision processes are used to formulate the problem. The survival function against hurricane is derived as a dynamic stress-strength model, and is incorporated in the proposed framework.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://Bug.EGR.UH.EDU/pipermail/engi-dist/attachments/20150416/54093445/attachment-0001.html 
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Doctoral Dissertation Defense.docx
Type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
Size: 15118 bytes
Desc: Doctoral Dissertation Defense.docx
Url : http://Bug.EGR.UH.EDU/pipermail/engi-dist/attachments/20150416/54093445/attachment-0001.bin